James G. Scott

发表

How Likely are Ride-share Drivers to Earn a Living Wage? Large-scale Spatio-temporal Density Smoothing with the Graph-fused Elastic Net

Mauricio Tec, Natalia Zuniga-Garcia, Randy B. Machemehl, 2019, 1911.08106.

Nonparametric Bayesian multiple testing for longitudinal performance stratification

James G. Scott, 2009, 1009.5869.

Polya-Gamma Data Augmentation for Dynamic Models

Liang Sun, James G. Scott, Jesse Windle, 2013 .

Fully Bayesian inference for neural models with negative-binomial spiking

James G. Scott, Jonathan W. Pillow, 2012, NIPS.

Erratum: A coherent approach for analysis of the Illumina HumanMethylation450 BeadChip improves data quality and performance in epigenome-wide association studies (vol 16, 37, 2015)

Weihua Zhang, James G. Scott, Mark I. McCarthy, 2016 .

Leaf-Smoothed Hierarchical Softmax for Ordinal Prediction

James G. Scott, Wesley Tansey, Karl Pichotta, 2018, AAAI.

Better Conditional Density Estimation for Neural Networks

James G. Scott, Wesley Tansey, Karl Pichotta, 2016 .

The Bayesian bridge

James G. Scott, Jesse Windle, Nicholas G. Polson, 2011, 1109.2279.

Flexible Learning on the Sphere Via Adaptive Needlet Shrinkage and Selection

James G. Scott, 2009 .

Sequential Nonparametric Tests for a Change in Distribution: An Application to Detecting Radiological Anomalies

James G. Scott, Alex Reinhart, Oscar Hernan Madrid Padilla, 2016 .

The DFS Fused Lasso: Linear-Time Denoising over General Graphs

James G. Scott, Ryan J. Tibshirani, James Sharpnack, 2016, J. Mach. Learn. Res..

Proximal Algorithms in Statistics and Machine Learning pdf

James G. Scott, Nicholas G. Polson, Brandon T. Willard, 2015, ArXiv.

Benchmarking historical corporate performance

James G. Scott, 2009, Comput. Stat. Data Anal..

Vertical-likelihood Monte Carlo Integration

James G. Scott, Nicholas G. Polson, 2014 .

Evaluation of ride-sourcing search frictions and driver productivity: A spatial denoising approach

Mauricio Tec, Natalia Zuniga-Garcia, James G. Scott, 2018, Transportation Research Part C: Emerging Technologies.

Multiscale Spatial Density Smoothing: An Application to Large-Scale Radiological Survey and Anomaly Detection

James G. Scott, Wesley Tansey, Alex Reinhart, 2015, 1507.07271.

Mixtures, envelopes and hierarchical duality

James G. Scott, Nicholas G. Polson, 2014, 1406.0177.

Regularization via Data Augmentation

James G. Scott, Nicholas G. Polson, 2011 .

Case studies in Bayesian screening for time-varying model structure: the partition problem

James G. Scott, Jesse Windle, Zesong Liu, 2013 .

Maximum-Variance Total Variation Denoising for Interpretable Spatial Smoothing

James G. Scott, Jesse Thomason, Wesley Tansey, 2018, AAAI.

False Discovery Rate Smoothing

Oluwasanmi Koyejo, Russell A. Poldrack, James G. Scott, 2014, Journal of the American Statistical Association.

Diet2Vec: Multi-scale analysis of massive dietary data pdf

James G. Scott, Edward W. Lowe, Wesley Tansey, 2016, ArXiv.

NONPARAMETRIC BAYESIAN MULTIPLE HYPOTHESIS TESTING OF AUTOREGRESSIVE TIME SERIES

James G. Scott, 2008 .

Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables

James G. Scott, Jesse Windle, Nicholas G. Polson, 2012, 1205.0310.

TDAstats: R pipeline for computing persistent homology in topological data analysis

Drew F. K. Williamson, James G. Scott, Raoul R. Wadhwa, 2018, J. Open Source Softw..

Nonparametric Benchmarking Using the Extended Rank Likelihood

James G. Scott, 2009 .

Architectural Building Codes: A Graphic Reference

James G. Scott, 1997 .

Handling Sparsity via the Horseshoe

James G. Scott, Carlos M. Carvalho, Nicholas G. Polson, 2009, AISTATS.

BART with targeted smoothing: An analysis of patient-specific stillbirth risk

James G. Scott, Carlos M. Carvalho, Jared S. Murray, 2018, The Annals of Applied Statistics.

Optimal post-selection inference for sparse signals: a nonparametric empirical Bayes approach

James G. Scott, Spencer Woody, Oscar Hernan Madrid Padilla, 2018, 1810.11042.

The horseshoe estimator for sparse signals

James G. Scott, Nicholas G. Polson, C. Carvalho, 2010 .

Feature-Inclusion Stochastic Search for Gaussian Graphical Models

James G. Scott, C. Carvalho, 2008 .

Local shrinkage rules, Lévy processes and regularized regression

James G. Scott, Nicholas G. Polson, 2010, 1010.3390.

On the half-cauchy prior for a global scale parameter

James G. Scott, Nicholas G. Polson, 2011, 1104.4937.

An exploration of aspects of Bayesian multiple testing

James G. Scott, J. Berger, 2006 .

A Fast and Flexible Algorithm for the Graph-Fused Lasso

James G. Scott, Wesley Tansey, 2015, 1505.06475.

Priors for Random Count Matrices Derived from a Family of Negative Binomial Processes

James G. Scott, Oscar Hernan Madrid Padilla, Mingyuan Zhou, 2014, 1404.3331.

Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem

James G. Scott, J. Berger, 2010, 1011.2333.

Objective Bayesian model selection in Gaussian graphical models

James G. Scott, C. Carvalho, 2009 .

Shrink Globally, Act Locally: Sparse Bayesian Regularization and Prediction

James G. Scott, M. J. Bayarri, Nicholas G. Polson, 2022 .

Expectation-maximization for logistic regression

James G. Scott, Liangrui Sun, 2013, 1306.0040.

Deep Nonparametric Estimation of Discrete Conditional Distributions via Smoothed Dyadic Partitioning

James G. Scott, Wesley Tansey, Karl Pichotta, 2017, 1702.07398.

Vertical-likelihood Monte Carlo

James G. Scott, Nicholas G. Polson, 2014, 1409.3601.

No Control Genes Required: Bayesian Analysis of qRT-PCR Data

James G. Scott, Mikhail V. Matz, M. Matz, 2013, PloS one.

Good, great, or lucky? Screening for firms with sustained superior performance using heavy-tailed priors

James G. Scott, Nicholas G. Polson, 2010, 1010.5223.

A deconvolution path for mixtures

James G. Scott, Nicholas G. Polson, Oscar Hernan Madrid Padilla, 2015, 1511.06750.

Alternative Global – Local Shrinkage Priors Using Hypergeometric – Beta Mixtures

James G. Scott, Nicholas G. Polson, 2009 .

Nonparametric Bayesian testing for monotonicity

Thomas S. Shively, Stephen G. Walker, James G. Scott, 2013, 1304.3378.

Large-scale simultaneous testing with hypergeometric inverted-beta priors

James G. Scott, Nicholas G. Polson, 2010 .

Modeling unobserved heterogeneity using finite mixture random parameters for spatially correlated discrete count data

James G. Scott, Jorge A Prozzi, Prasad Buddhavarapu, 2016 .

Sampling P olya-Gamma random variates: alternate and approximate techniques

James G. Scott, Jesse Windle, Nicholas G. Polson, 2014, 1405.0506.

The partition problem: case studies in Bayesian screening for time-varying model structure

James G. Scott, Jesse Windle, Zesong Liu, 2011 .

Multiple Testing , Empirical Bayes , and the Variable-Selection Problem

James G. Scott, JAMES G. SCOTT, 2008 .

Interpretable Low-Dimensional Regression via Data-Adaptive Smoothing

James G. Scott, Jesse Thomason, Wesley Tansey, 2017, 1708.01947.

GapTV: Accurate and Interpretable Low-Dimensional Regression and Classification

James G. Scott, Wesley Tansey, 2017, 1702.07405.

Parameter expansion in local-shrinkage models

James G. Scott, 2010, 1010.5265.

NONPARAMETRIC MULTIPLE TESTING OF TIME SERIES 15 GV Company Name Flat 1 Flat 2 GP 7 GP 8 Other Null

James G. Scott, 2008 .

The DFS fused lasso: nearly optimal linear-time denoising over graphs and trees

James G. Scott, Ryan J. Tibshirani, James Sharpnack, 2016 .

Bayesian Estimation of Intensity Surfaces on the Sphere via Needlet Shrinkage and Selection

James G. Scott, 2011 .

Explosive Volatility: A Model of Financial Contagion

James G. Scott, Nicholas G. Polson, 2011 .

A projection approach for multiple monotone regression

James G. Scott, C. Carvalho, Lizhen Lin, 2019, 1911.07553.

A recursive estimate for the predictive likelihood in a topic model

Jason Baldridge, James G. Scott, James Scott, 2013, AISTATS.

The partition problem: case studies in Bayesian screening for time-varying model structure

James G. Scott, J. Windle, Zesong Liu, 2011, 1111.0617.

Nonparametric density estimation by histogram trend filtering

James G. Scott, Oscar Hernan Madrid Padilla, 2015, 1509.04348.

Sparse Bayes estimation in non-Gaussian models via data augmentation

James G. Scott, Nicholas G. Polson, 2011 .

Data augmentation for non-Gaussian regression models using variance-mean mixtures

James G. Scott, Nicholas G. Polson, 2011, 1103.5407.

False Discovery Rate Regression: An Application to Neural Synchrony Detection in Primary Visual Cortex

James G. Scott, Robert E Kass, Pengcheng Zhou, 2013, Journal of the American Statistical Association.

Large-Scale Spatiotemporal Density Smoothing with the Graph-fused Elastic Net: Application to Ride-sourcing Driver Productivity Analysis.

James G. Scott, R. Machemehl, Natalia Zuniga-Garcia, 2019 .

Default Bayesian analysis for multi-way tables: a data-augmentation approach

James G. Scott, Nicholas G. Polson, 2011, 1109.4180.

Efficient Data Augmentation in Dynamic Models for Binary and Count Data

James G. Scott, C. Carvalho, Liangrui Sun, 2013, 1308.0774.

Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables

James G. Scott, Nicholas G. Polson, Jesse Windle, 2012, 1205.0310.

Tensor Decomposition With Generalized Lasso Penalties

James G. Scott, Oscar Hernan Madrid-Padilla, James Scott, 2015, 1502.06930.

An empirical test for Eurozone contagion using an asset-pricing model with heavy-tailed stochastic volatility

James G. Scott, Nicholas G. Polson, 2011, 1110.5789.

Multiple Testing and the Variable-Selection Problem

James G. Scott, 2008 .